Random sampling algorithm for multi-agent cooperation planning

Shotaro Kamio, H. Iba
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引用次数: 16

Abstract

The cooperation of several robots is needed for complex tasks. The cooperation methods for multiple robots generally require exact goal or sub-goal positions. However, it is difficult to direct the goal or sub-goal positions to multiple robots for the sake of cooperation with each other. Planning algorithms reduce the burden for this purpose. In this paper, we propose a multi-agent planning algorithm based on a random sampling method. This method doesn't require the exact sub-goal positions nor the times at which cooperation occurs. The effectiveness of this approach is empirically shown by simulation results.
多智能体协作规划的随机抽样算法
复杂的任务需要多个机器人的合作。多机器人的协作方法一般需要精确的目标或子目标位置。然而,为了实现机器人之间的相互协作,很难将目标或子目标位置直接分配给多个机器人。规划算法减轻了这方面的负担。本文提出了一种基于随机抽样方法的多智能体规划算法。这种方法不需要精确的子目标位置,也不需要合作发生的时间。仿真结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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